The present invention relates to the field of positron imaging, and more particularly to the field of positron emission tomography. The invention is also applicable to other fields in where it is necessary to estimate the contribution of randoms in data indicative of positron coincidence events.
Positron emission tomography (PET) is a branch of nuclear medicine in which a positron-emitting radiopharmaceutical such as .sup.18 F-fluorodeoxyglucose (FDG) is introduced into the body of a patient. Each emitted positron reacts with an electron in what is known as an annihilation event, thereby simultaneously generating a pair of 511 keV gamma rays. The gamma rays are emitted in directions approximately 180.degree. apart, i.e. in opposite directions.
A pair of detectors registers the position and energy of the respective gamma rays, thereby providing information as to the position of the annihilation event and hence the positron source. Because the gamma rays travel in opposite directions, the positron annihilation is said to have occurred along a line of response (LOR) connecting the detected gamma rays. A number of such events are collected and used to reconstruct a clinically useful image.
One factor which degrades image quality in PET imaging is random events. The 511 keV gamma rays generated by the positron annihilations are detected within a narrow coincidence timing window. Pairs of such gamma rays detected within this timing window are ordinarily considered to be coincident and are used to generate an image. However, some of these events result from what are known as random events. A random event is one in which a pair of gamma rays from two unrelated annihilation events are detected in coincidence. Thus, the acquired coincidence data includes both true and random events. Because the LORs for the random events do not represent actual positron annihilations, the randoms introduce noise into the acquired data, thereby degrading image quality.
Various techniques have been used to minimize the deleterious effects of random events. Because the number of randoms increases with the square of activity, one technique is to image at relatively low activity levels. While relatively fewer randoms are detected, an undesirable side effect of this technique is that fewer true coincidence events are available to generate the image.
Another technique for estimating the contribution of randoms is to delay the signal from one of the detectors by an amount longer than the coincidence timing window prior to applying the coincidence check. Due to the delay, events which are detected by a pair of detectors within the coincidence timing window (i.e., in coincidence) represent randoms. The collected events are rebinned and used to correct the acquired coincidence data. A particular drawback to such a delayed correction technique is that the rate of randoms collection is the same as that of the true event collection. This technique also has a deleterious effect on image noise characteristics.
Yet another technique is to determine the random coincidence rate based on the singles rates of the system's detectors and the length of the coincidence timing window. According to one technique, the system detectors have been treated as a plurality of virtual subdetectors, and the singles rate for each of the subdetectors has been measured. The singles rates for the various combinations of subdetectors has in turn been used to generate a randoms sinogram. One disadvantage to such a technique is that it is necessary to collect data additional to the desired coincidence data. Yet another disadvantage is that improving the accuracy of the estimation requires that the detectors be divided into arbitrarily small subdetectors.